Investigative studies of white matter structures using tractography often require manual virtual bundle dissection to be performed. Human errors and personal decisions make these manual segmentations hard to reproduce. Reproducibility assessment of raters is common practice in other neuroimaging field where segmentation protocols were refined to maximize reproducibility. However, this has not been done in the field of diffusion tractography. The contribution of this study is to provide the first large-scale, multi-center variability assessment of virtual dissection of tractography dataset.